We're hiring a Senior Quality Engineer to build and own quality systems behind our AI system. You'll define how we verify correctness, automate confidence, and enforce engineering standards. You'll work alongside a small team of software engineers and own the engineering systems that make fast development possible without sacrificing quality.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Company Description:
Hyly.AI is multifamily’s only Intelligence Fabric™, weaving Artificial, Business, and Human intelligence into one operating system for growth. The company connects raw data to decisions, decisions to actions, and actions to measurable outcomes, turning complexity into clarity. Founded in 2010, Hyly.AI has been helping multifamily leaders scale operations and marketing without adding extra headcount. Today, 4 of the top 5 National Multifamily Housing Council (NMHC) managers rely on Hyly.AI to power their growth by transforming data into actionable insights and structured processes.
Job Summary:
We're building an AI system that reads live advertising performance, decides what to optimize, and acts on it — automatically, shipping new capability every day. We're hiring the first engineer dedicated to building and owning the quality systems behind it.
This role goes well beyond testing. You'll define how we verify correctness, automate confidence, enforce engineering standards, and make it safe to ship AI-powered software daily. You'll work alongside a small team of software engineers and own the engineering systems that make fast development possible without sacrificing quality. In a system that spends real budget on its own decisions, a feature can run perfectly and still be wrong — a metric that lands a conversion off from the ad platform, a threshold computed at the wrong level of aggregation, a recommendation that flags a customer's own brand searches as "waste." Preventing and catching that class of failure is what this role is built around.
We're not looking for someone to manually test features after they're built. We're looking for an engineer who believes quality should be designed into the development process — through automation, tooling, strong engineering practices, and AI-assisted workflows. If your first instinct is to build systems that prevent bugs rather than just find them, you'll thrive here.
How We Build Software
We don't run a traditional QA process with sprint-end testing and manual verification. We ship continuously — often several times a day — with AI-assisted development woven through our engineering workflow. The goal is a semi-autonomous software factory where quality is embedded through automation, evaluation, and engineering discipline, not manual checklists. Success here means building systems that make bugs hard to introduce, regressions easy to detect, and deployments safe to run fast.
Must-Have Qualifications:
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- Strong software engineering experience building automation, testing infrastructure, developer tooling, or quality systems (typically 5+ years)
- Strong Python engineering — you write, debug, and contribute production code, not only test scripts
- Experience designing automated testing frameworks, not just executing tests
- Experience building or maintaining CI/CD pipelines (GitHub Actions or similar)
- Strong SQL and data-validation skills
- Daily use of AI-assisted development tools (Claude Code, Cursor, Codex, Gemini CLI, or similar) for real engineering work
- Comfortable reviewing pull requests and improving engineering workflows
- Comfortable owning quality solo in a fast team shipping continuously
Job Responsibilities:
- Validate the correctness of recommendations, analytics, and automated decisions — not just that they render
- Design and build automated testing across unit, integration, API, end-to-end, and AI-evaluation layers
- Own CI/CD pipelines, release gates, and deployment quality for the engineering team
- Establish engineering quality standards across the monorepo — automated checks, repository discipline, merge requirements
- Build developer tooling that raises engineering velocity while keeping confidence high in every release
- Design regression suites, golden datasets, and evaluation frameworks for both deterministic and AI-generated functionality
- Partner with engineers during feature development — reviewing architecture and making systems testable from the start
- Contribute production code where it helps, especially in quality infrastructure and backend systems
- Continuously improve how the team ships — automating repetitive engineering work and introducing AI-assisted practices so quality becomes an automatic outcome of development
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Preferred (Nice-to-Have) Qualifications:
- Experience building quality systems for AI or data-intensive products
- Experience evaluating LLM or non-deterministic AI systems
- Experience working in monorepos
- Familiarity with GitHub Actions or similar CI/CD platforms
- Experience with performance-marketing or analytics platforms (Google Ads a plus)
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